globalchange  > 气候变化事实与影响
DOI: 10.1016/j.jag.2014.06.001
Scopus记录号: 2-s2.0-84920702831
论文题名:
A total variation model based on edge adaptive guiding function for remote sensing image de-noising
作者: Wang X; , Liu Y; , Zhang H; , Fang L
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2015
卷: 34, 期:1
起始页码: 89
结束页码: 95
语种: 英语
英文关键词: De-noising ; Edge adaptive guiding function ; Remote sensing image ; Standard gradient ; Total variation
Scopus关键词: efficiency measurement ; filter ; remote sensing ; satellite imagery ; smoothing ; texture
英文摘要: The unexpected noise generated during the process of remote sensing images formation and transmission process is a main factor undermining the images' quality and usage. In recent years, thanks to its local self-adapting characteristics, formal normalization, and modeling flexibility, PDE has received wide attention for its image de-noising functions, thus pushing the realization of maintaining image details while successfully de-noising a new goal for remote sensing images filtering. Having firstly analyzed and discussed the TV model and M model, a modified variation-model (S model for short) based on edge adaptive guiding function is proposed in this paper. The model introduces edge adaptive guiding function based on the standard gradient into the non-linear diffusion term and reconstructed approaching term, which adaptively adjust the smooth intensity around edge and texture information-rich regions of remote sensing images. S-model does not only overcome staircase effect that is easily produced in the TV model, but also avoids losing details and texture information which is often seen in M model,it can efficiently eliminate noises, maintain a good image edge and keep texture details perfectly. The experimental results validate the effectiveness and stability of the proposed model. © 2014 Published by Elsevier B.V.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79508
Appears in Collections:气候变化事实与影响

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作者单位: Department of Computer and Information Technology, Liaoning Normal University, Dalian City, Liaoning Province, China; Department of Mathematics, Liaoning Normal University, Dalian City, Liaoning Province, China; Department of Mathematics, Tonghua Teachers College, Tonghua City, Jilin Province, China; Department of Computer Science and Technology, Soochow University, Suzhou City, Jiangsu Province, China

Recommended Citation:
Wang X,, Liu Y,, Zhang H,et al. A total variation model based on edge adaptive guiding function for remote sensing image de-noising[J]. International Journal of Applied Earth Observation and Geoinformation,2015-01-01,34(1)
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